Level set method for positron emission tomography
Chan, Tony F.
Tai, Xue Cheng
Date of Issue2007
School of Physical and Mathematical Sciences
In positron emission tomography (PET), a radioactive compound is injected into the body to promote a tissue-dependent emission rate. Expectation maximization (EM) reconstruction algorithms are iterative techniques which estimate the concentration coefficients that provide the best fitted solution, for example, a maximum likelihood estimate. In this paper, we combine the EM algorithm with a level set approach. The level set method is used to capture the coarse scale information and the discontinuities of the concentration coefficients. An intrinsic advantage of the level set formulation is that anatomical information can be efficiently incorporated and used in an easy and natural way. We utilize a multiple level set formulation to represent the geometry of the objects in the scene. The proposed algorithm can be applied to any PET configuration, without major modifications.
International Journal of Biomedical Imaging.
International Journal of Biomedical Imaging © copyright 2007 Hindawi Publishing Corporation. The journal's website is located at http://www.hindawi.com/journals/ijbi/.